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By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely used statistical technique is accessible to readers who may have only a rudimentary knowledge of mathematics. Chapters discuss: -descriptive statistics using vector notation and the components of a simple regression model; -the logic of sampling distributions and simple hypothesis testing; -the basic operations of matrix algebra and the properties of the multiple regression model; -testing compound hypotheses and the application of the regression model to the analyses of variance and covariance, and -structural equation models and influence statistics.
By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely
Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Neg
Understanding Regression Analysis: An Introductory Guide by Larry D. Schroeder, David L. Sjoquist, and Paula E. Stephan presents the fundamentals of regression
Providing beginners with a background to the frequently-used technique of linear regression, this text provides a heuristic explanation of the procedures and te
The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged
